The present invention relates to determining the state-of-health (SOH) of an electrochemical device. More particularly, the present invention relates to determining the SOH of an electrochemical device using an intelligent system, e.g. a fuzzy logic system.
The SOH of a battery has been interpreted in different ways by scientists/engineers in the field. In the case of valve regulated lead acid (VRLA) batteries used by utility companies, for providing emergency backup power, SOH is interpreted to mean that a battery is close to the end of its cycle life and needs replacement. Several papers including Feder and Hlavac 1994 INTELEC Conf. Proc. pp. 282-291 (1994) and Hawkins and Hand 1996 INTELEC Conf. Proc. pp. 640-645 (1996) demonstrate that the increase in impedance of aging VRLA batteries can be used to indicate the SOH of the battery.
Another interpretation of battery SOH is the capability of a battery to meet its load demand. This is also referred to as xe2x80x9cbattery conditionxe2x80x9d by others in the field. To obtain the SOH of a battery in the terms defined, both the available charge capacity of the battery and the maximum power available from the battery are required. Several approaches have been used to determine the condition of a battery. In U.S. Pat. No. 5,365,453 is described a method in which a ratio of a change in battery voltage to a change in load is used to predict impending battery failure in battery powered electronic devices. Similar methods in which the battery response to and recovery from the application of a load is used to determine the SOH of batteries are reported in U.S. Pat. Nos. 4,080,560 and 5,159,272. While these load profiling approaches work reasonably well for batteries integrated into a system, they are not necessarily accurate or reliable ways of determining the SOH of batteries outside a system.
The above-discussed and other drawbacks and deficiencies of the prior art are overcome or alleviated by the method for determining state of health (SOH) of an electrochemical device using an intelligent system, e.g., a fuzzy logic system, of the present invention. In accordance with the present invention, the state of health of an electrochemical device is determined by an internal characteristic parameters (or external operating and environmental conditions) of the electrochemical device and characteristic parameters of a load and the SOH of the electrochemical device with an intelligent system. The electrochemical device comprises such devices as primary (xe2x80x9cthrowawayxe2x80x9d) batteries, rechargeable batteries, fuel cells, a hybrid battery containing a fuel cell electrode and electrochemical supercapacitors. The intelligent system is trained in the relationship between characteristic parameters of the electrochemical device, characteristic parameters of the load and the SOH of the electrochemical device.
The intelligent system comprises any system that adaptively estimates or learns continuous functions from data without specifying how outputs depend on inputs. By way of example, the intelligent system includes an artificial neural system, a fuzzy system and other such model-free function estimators that learn. Learning, so-called, xe2x80x9ctunesxe2x80x9d an intelligent system. This learning process (also referred to as a training process) can be implemented in many ways. The intelligent system can be implemented using: an algorithm such as radiant descent and clustering used to tune neural networks and adaptive fuzzy systems; search optimization techniques such as those used by genetic algorithms; or an expert""s guesses or trials and errors such as those used in fuzzy expert systems and fuzzy systems.